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3 results for “hedonic price”
Data associated to "The Direct Cost of Contaminated Brownfield Sites on Real Estate in France: A Quasi-Exhaustive Hedonic Price Analysis"
<p>Data for replication of main results in "The Direct Cost of Contaminated Brownfield Sites on Real Estate in France: A Quasi-Exhaustive Hedonic Price Analysis". The folder "data_estim" contains all necessary data to replicate all estimations in the article (see the R code "codes_cbs-cost") with three .csv files: dvf_estim.csv, dvfbasol_estim.csv and cell200_simulation.csv. The variable names in these files are as follow:</p><p> </p><p>Identifier Variables:</p><p>- IDMUTATION: identifier for each transacted property</p><p>- comm_code: identifier for each commune defined in 2021</p><p>- admin_code: identifier for urban areas defined in 2021</p><p>- iris2014_code: identifier for each neighborhood defined in 2014</p><p>- cell200_code: identifier for each 200-meters gredded cells</p><p>- dvf_x: longitude of each transacted property (EPSG: 2154, Lambert-93, RGF93)</p><p>- dvf_y: latitude of each transacted property (EPSG: 2154, Lambert-93, RGF93)</p><p>- basol_code: identifier for each CBS (only reported in dvfbasol_estim.csv)</p><p>- anneemut: year of transaction for each property</p><p> </p><p>Dependent Variable:</p><p>- pm2: price in euro per square meter of transacted properties</p><p> </p><p>Interest Variables:</p><p>- areaha_basol250: area in hectare of CBS between 0 and 250 meters from transacted property</p><p>- areaha_basol500: area in hectare of CBS between 250 and 500 meters from transacted property</p><p>- areaha_basol1000: area in hectare of CBS between 500 and 1000 meters from transacted property</p><p>- areaha_basol2000: area in hectare of CBS between 1000 and 2000 meters from transacted property</p><p>- areaha_basol3000: area in hectare of CBS between 2000 and 3000 meters from transacted property</p><p>- area250_indpro: area in hectare of CBS with industrial manufacturing activities between 0 and 250 meters from transacted property</p><p>- area500_indpro: area in hectare of CBS with industrial manufacturing activities between 250 and 500 meters from transacted property</p><p>- area1000_indpro: area in hectare of CBS with industrial manufacturing activities between 500 and 1000 meters from transacted property</p><p>- area2000_indpro: area in hectare of CBS with industrial manufacturing activities between 1000 and 2000 meters from transacted property</p><p>- area3000_indpro: area in hectare of CBS with industrial manufacturing activities between 2000 and 3000 meters from transacted property</p><p>- area250_indoth: area in hectare of CBS with industrial non-manufacturing activities (extractive) between 0 and 250 meters from transacted property</p><p>- area500_indoth: area in hectare of CBS with industrial non-manufacturing activities (extractive) between 250 and 500 meters from transacted property</p><p>- area1000_indoth: area in hectare of CBS with industrial non-manufacturing activities (extractive) between 500 and 1000 meters from transacted property</p><p>- area2000_indoth: area in hectare of CBS with industrial non-manufacturing activities (extractive) between 1000 and 2000 meters from transacted property</p><p>- area3000_indoth: area in hectare of CBS with industrial non-manufacturing activities (extractive) between 2000 and 3000 meters from transacted property</p><p>- area250_othact: area in hectare of CBS with other or unknown activities between 0 and 250 meters from transacted property</p><p>- area500_othact: area in hectare of CBS with other or unknown activities between 250 and 500 meters from transacted property</p><p>- area1000_othact: area in hectare of CBS with other or unknown activities between 500 and 1000 meters from transacted property</p><p>- area2000_othact: area in hectare of CBS with other or unknown activities between 1000 and 2000 meters from transacted property</p><p>- area3000_othact: area in hectare of CBS with other or unknown activities between 2000 and 3000 meters from transacted property</p><p>- areaha_specific250: area in hectare of CBS specific to a unique CBS between 0 and 250 meters from transacted property (only reported in dvfbasol_estim.csv)</p><p>- areaha_specific500: area in hectare of CBS specific to a unique CBS between 250 and 500 meters from transacted property (only reported in dvfbasol_estim.csv)</p><p>- areaha_specific1000: area in hectare of CBS specific to a unique CBS between 500 and 1000 meters from transacted property (only reported in dvfbasol_estim.csv)</p><p>- areaha_specific2000: area in hectare of CBS specific to a unique CBS between 1000 and 2000 meters from transacted property (only reported in dvfbasol_estim.csv)</p><p> </p><p>Robustness Variables:</p><p>- pm2mean_iris: average transaction price per square meter of neighborhood IRIS</p><p>- shpoorhouse: share in percentage of poor households </p><p>- dvfschool_nb250: number of schools within 250 meters of property</p><p>- dvfschool_nb500: number of schools within 500 meters of property</p><p>- dvfschool_nb1000: number of schools within 1000 meters of property</p><p>- dvfschool_nb2000: number of schools within 2000 meters of property</p><p>- dvfschool_nb3000: number of schools within 3000 meters of property</p><p>- dvfroad_nb250: number of road connections within 250 meters of property</p><p>- dvfroad_nb500: number of road connections within 500 meters of property</p><p>- dvfroad_nb1000: number of road connections within 1000 meters of property</p><p>- dvfroad_nb2000: number of road connections within 2000 meters of property</p><p>- dvfroad_nb3000: number of road connections within 30000 meters of property</p><p>- dvfrail_nb250: number of railway stations within 250 meters of property</p><p>- dvfrail_nb500: number of railway stations within 500 meters of property</p><p>- dvfrail_nb1000: number of railway stations within 1000 meters of property</p><p>- dvfrail_nb2000: number of railway stations within 2000 meters of property</p><p>- dvfrail_nb3000: number of railway stations within 3000 meters of property</p><p> </p><p>Control Variables:</p><p>- center_dist: distance in kilometers of transacted property from urban area center</p><p>- sterr: surface area in square meter of parcel of each property</p><p>- sbati: surface area in square meter of building surfaces</p><p>- vente_cla: transaction through a classical process (binary variable)</p><p>- vente_adj: transaction through adjudicated process (binary variable)</p><p>- vente_ech: transaction through special exchange process (binary variable)</p><p>- vente_exp: transaction through expropriation process (binary variable)</p><p>- vente_efa: transaction before completion (binary variable)</p><p>- nblocmai: number of houses in each transaction</p><p>- nblocapt: number of apartments in each transaction</p><p>- nblocdep: number of building dependencies in each transaction</p><p>- nblocact: number of properties for commercial purpose in each transaction</p><p>- nbapt1pp: number of apartment with 1 room in each transaction</p><p>- nbapt2pp: number of apartment with 2 rooms in each transaction</p><p>- nbapt3pp: number of apartment with 3 rooms in each transaction</p><p>- nbapt4pp: number of apartment with 4 rooms in each transaction</p><p>- nbapt5pp: number of apartment with 5 and more rooms in each transaction</p><p>- nbmai1pp: number of house with 1 room in each transaction</p><p>- nbmai2pp: number of house with 2 rooms in each transaction</p><p>- nbmai3pp: number of house with 3 rooms in each transaction</p><p>- nbmai4pp: number of house with 4 rooms in each transaction</p><p>- nbmai5pp: number of house with 5 and more rooms in each transaction</p><p>- pm2mean_comm: average transaction price in euro per square meter of commune</p><p>- dvfmonument_nb500: number of historical monuments between 0 and 500 meters from transacted property</p><p>- dvfmonument_nb1000: number of historical monuments between 500 and 1000 meters from transacted property</p><p>- dvfmonument_nb2000: number of historical monuments between 1000 and 2000 meters from transacted property</p><p>- dvfindus_nb500: number of active industrial sites between 0 and 500 meters from transacted property</p><p>- dvfindus_nb1000: number of active industrial sites between 500 and 1000 meters from transacted property</p><p>- dvfindus_nb2000: number of active industrial sites between 1000 and 2000 meters from transacted property</p><p>- sh_apt: share of apartments in neighborhood IRIS</p><p>- sh_1945: share in percentage of properties with a building age before 1945</p><p>- sh_1970: share in percentage of properties with a building age before 1970</p><p>- sh_1990: share in percentage of properties with a building age before 1990</p><p>- sh_ap90: share in percentage of properties with a building age between 1990 and 2015</p><p>- sh_2015: share in percentage of properties with a building age after 2015</p><p>- clc1000_urbanhousing: share in percentage of land within 1000 meters of transacted properties with housing</p><p>- clc1000_urbanpark: share in percentage of land within 1000 meters of transacted properties with urban parks</p><p>- clc1000_recreation: share in percentage of land within 1000 meters of transacted properties with recreative activities</p><p>- clc1000_industrial: share in percentage of land within 1000 meters of transacted properties with industrial activities</p><p>- clc1000_transport: share in percentage of land within 1000 meters of transacted properties with transport infrastructures</p><p>- clc1000_nature: share in percentage of land within 1000 meters of transacted properties with natural land use</p><p>- clc1000_agr: share in percentage of land within 1000 meters of transacted properties with agricultural land use</p><p>- clc1000_forest: share in percentage of land within 1000 meters of transacted properties with forest</p><p>- clc1000_water: share in percentage of land within 1000 meters of transacted properties with water</p><p> </p><p> </p>
Dataset Questionnaire Driving Repeat Purchases and E-WOM: How Price, Reputation, Hedonic Appeal, and Social Interaction Shape Consumer Behavior in Indonesia's E-Commerce Smartphone Market
<p>The following dataset is a dataset from a study that investigated price advantage, reputation, hedonic effort, and social interaction influence customer satisfaction, which in turn impacts repurchase intention and e-WOM (electronic word-of-mouth).</p>
Spatial Heterogeneity in Hedonic Price Effects for Lake Water Quality
<p>This database provides model results, elasticity estimates, and descriptive statistics for output from Spatial Heterogeneity in Hedonic Price Effects for Lake Water Quality manuscript. DOI: https://doi.org/10.3368/le.100.1.102122-0086R</p>
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